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Found 7 papers, 3 papers with code
Pixel-weighted Multi-pose Fusion for Metal Artifact Reduction in X-ray Computed Tomography
X-ray computed tomography (CT) reconstructs the internal morphology of a three dimensional object from a collection of projection images, most commonly using a single rotation axis.
Autonomous Polycrystalline Material Decomposition for Hyperspectral Neutron Tomography
The algorithm estimates the linear attenuation coefficient spectra from the measured radiographs and then uses these spectra to perform polycrystalline material decomposition and reconstructs 3D material volumes to localize materials in the spatial domain.
An Edge Alignment-based Orientation Selection Method for Neutron Tomography
Neutron computed tomography (nCT) is a 3D characterization technique used to image the internal morphology or chemical composition of samples in biology and materials sciences.
Multi-Pose Fusion for Sparse-View CT Reconstruction Using Consensus Equilibrium
In this paper, we present Multi-Pose Fusion, a novel algorithm that performs a joint tomographic reconstruction from CT scans acquired from multiple poses of a single object, where each pose has a distinct rotation axis.
Ensemble Wrapper Subsampling for Deep Modulation Classification
Subsampling of received wireless signals is important for relaxing hardware requirements as well as the computational cost of signal processing algorithms that rely on the output samples.
Fast Deep Learning for Automatic Modulation Classification
We then study algorithms to reduce the training time by minimizing the size of the training data set, while incurring a minimal loss in classification accuracy.
Deep Neural Network Architectures for Modulation Classification
Finally, we introduce a Convolutional Long Short-term Deep Neural Network (CLDNN [4]) to achieve an accuracy of approximately 88. 5% at high SNR.
